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NY Times 23 Sept 2008 - time series of the day. Stat 153 - 23 Sept 2008 D. R. Brillinger Chapter 4 - Fitting t.s. models in the time domain sample autocovariance.

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Presentation on theme: "NY Times 23 Sept 2008 - time series of the day. Stat 153 - 23 Sept 2008 D. R. Brillinger Chapter 4 - Fitting t.s. models in the time domain sample autocovariance."— Presentation transcript:

1 NY Times 23 Sept 2008 - time series of the day

2 Stat 153 - 23 Sept 2008 D. R. Brillinger Chapter 4 - Fitting t.s. models in the time domain sample autocovariance coefficient. Under stationarity,...

3 Estimated autocorrelation coefficient asymptotically normal interpretation

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5 Uses of acf mixing (asymptotically independent)? MA(q)? Seasonal component? ergodic

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8 Estimating the mean Can be bigger or less than  2 /N

9 Fitting an autoregressive, AR(p) Easy. Remember regression and least squares normal equations

10 AR(1) Cp.

11 Fitting an MA(q). Later. There is an R program Fitting an ARMA(p,q). Later. There is an R program Estimating p, q, (p,q). Later. There is a criterion.

12 Seasonal ARIMA. seasonal parameter s SARIMA(p,d,q)  (P,D,Q) s Example

13 Residual analysis. Paradigm observation = fitted value plus residual The parametric models have contained Z t

14 Plot residuals vs. t Acf of residuals

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25 Portmanteau lack-of-fit statistic ARMA(p,q) appropriate?

26 Model building (1) model formulation (2) model estimation (3) model checking All models are wrong but some are useful


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